Image-based rock typing using grain geometry features

[1]  Benoît Petri,et al.  3D rock fabric analysis using micro-tomography: An introduction to the open-source TomoFab MATLAB code , 2020, Comput. Geosci..

[2]  H. Sebastian Seung,et al.  Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification , 2017, Bioinform..

[3]  Shuyu Sun,et al.  Numerical Modeling and Simulation of Shale-Gas Transport with Geomechanical Effect , 2018, Transport in Porous Media.

[4]  H. Wadell,et al.  Volume, Shape, and Roundness of Quartz Particles , 1935, The Journal of Geology.

[5]  Haim J. Wolfson,et al.  Texture classification in aerial photographs and satellite data , 1992 .

[6]  Jules-Raymond Tapamo,et al.  A texture-based method for document segmentation and classification , 2006, South Afr. Comput. J..

[7]  Tao Zhang,et al.  Flow Mechanism and Simulation Approaches for Shale Gas Reservoirs: A Review , 2018, Transport in Porous Media.

[8]  Ozkan Kafadar,et al.  Application of edge detection to potential field data using eigenvalue analysis of structure tensor , 2012 .

[9]  Ajoy Kumar Ray,et al.  Texture Classification Using a Novel, Soft-Set Theory Based Classification Algorithm , 2006, ACCV.

[10]  Christoph H. Arns,et al.  Three-dimensional porous structure reconstruction based on structural local similarity via sparse representation on micro-computed-tomography images , 2018, Physical Review E.

[11]  M. A. Shaban,et al.  Textural classification of high resolution digital satellite imagery , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

[12]  Vladimir Vapnik,et al.  Support-vector networks , 2004, Machine Learning.

[13]  Aggelos K. Katsaggelos,et al.  Hybrid image segmentation using watersheds and fast region merging , 1998, IEEE Trans. Image Process..

[14]  C. Arns,et al.  Rock-typing Using The Complete Set Of Additive Morphological Descriptors , 2013 .

[15]  Philippe Renard,et al.  Connectivity metrics for subsurface flow and transport , 2013 .

[16]  Snehamoy Chatterjee Vision-based rock-type classification of limestone using multi-class support vector machine , 2012, Applied Intelligence.

[17]  Shuyu Sun,et al.  Flow and Transport in Porous Media: A Multiscale Focus , 2017 .

[18]  Linqi Zhu,et al.  Application of Multiboost-KELM algorithm to alleviate the collinearity of log curves for evaluating the abundance of organic matter in marine mud shale reservoirs: a case study in Sichuan Basin, China , 2018, Acta Geophysica.

[19]  D. Powers Evaluation: From Precision, Recall and F-Factor to ROC, Informedness, Markedness & Correlation , 2008 .

[21]  D. Healy,et al.  Anisotropic pore fabrics in faulted porous sandstones , 2017 .

[22]  Christoph H. Arns,et al.  Characterisation of irregular spatial structures by parallel sets and integral geometric measures , 2004 .

[23]  Christoph Georg Eichkitz,et al.  Grey level co-occurrence matrix and its application to seismic data , 2015 .

[24]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Renguang Zuo,et al.  Mapping Himalayan leucogranites using a hybrid method of metric learning and support vector machine , 2020, Comput. Geosci..

[26]  R A Young,et al.  The Gaussian derivative model for spatial vision: I. Retinal mechanisms. , 1988, Spatial vision.

[27]  Kevin Bouchard,et al.  Mineral grains recognition using computer vision and machine learning , 2019, Comput. Geosci..

[28]  Kim L. Boyer,et al.  The laplacian-of-gaussian kernel: A formal analysis and design procedure for fast, accurate convolution and full-frame output , 1989, Comput. Vis. Graph. Image Process..

[29]  Nishank Saxena,et al.  Compressibility predictions using digital thin-section images of rocks , 2020, Comput. Geosci..

[30]  Farshad Tajeripour,et al.  Developing a Novel Approach for Stone Porosity Computing Using Modified Local Binary Patterns and Single Scale Retinex , 2014 .

[31]  K. Mecke,et al.  Characterization of the dynamics of block copolymer microdomains with local morphological measures. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[32]  Dino Isa,et al.  An enhanced Support Vector Machine classification framework by using Euclidean distance function for text document categorization , 2011, Applied Intelligence.

[33]  Christoph H. Arns,et al.  Porous Structure Reconstruction Using Convolutional Neural Networks , 2018, Mathematical Geosciences.

[34]  Sam Kwong,et al.  A new method for multi-class support vector machines by training least number of classifiers , 2011, 2011 International Conference on Machine Learning and Cybernetics.

[35]  Renguang Zuo,et al.  Support vector machine: A tool for mapping mineral prospectivity , 2011, Comput. Geosci..

[36]  Fuyong Wang,et al.  Fracture and vug characterization and carbonate rock type automatic classification using X-ray CT images , 2017 .

[37]  Andreu Català,et al.  K-SVCR. A support vector machine for multi-class classification , 2003, Neurocomputing.

[38]  M. Pirrone,et al.  Lithofacies Classification of Thin-Layered Turbidite Reservoirs Through the Integration of Core Data and Dielectric-Dispersion Log Measurements , 2016 .

[39]  Hélio Lopes,et al.  LSHSIM: A Locality Sensitive Hashing based method for multiple-point geostatistics , 2017, Comput. Geosci..

[40]  C. Arns,et al.  A fast FFT method for 3D pore-scale rock-typing of heterogeneous rock samples via Minkowski functionals and hydraulic attributes , 2020, E3S Web of Conferences.

[41]  Jie Zhang,et al.  Generating porosity spectrum of carbonate reservoirs using ultrasonic imaging log , 2018, Acta Geophysica.

[42]  Rosziati Ibrahim,et al.  A Framework for Medical Images Classification Using Soft Set , 2013 .

[43]  Christoph H. Arns,et al.  Semi-quantitative multiscale modelling and flow simulation in a nanoscale porous system of shale , 2018, Fuel.

[44]  Scott T. Acton,et al.  Diffusion Partial Differential Equations for Edge Detection , 2009 .

[45]  Joan Serrat,et al.  Segmentation of petrographical images of marbles , 1996 .

[46]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[47]  LeeAnn Srogi,et al.  Phase Composition Maps integrate mineral compositions with rock textures from the micro-meter to the thin section scale , 2017, Comput. Geosci..

[48]  Emanuele Menegatti,et al.  Different Approaches for Extracting Information from the Co-Occurrence Matrix , 2013, PloS one.

[49]  Le Yu,et al.  Towards automatic lithological classification from remote sensing data using support vector machines , 2010, Comput. Geosci..

[50]  T. D. Jobe,et al.  Geological Feature Prediction Using Image-Based Machine Learning , 2018 .

[51]  Peter Christen,et al.  A note on using the F-measure for evaluating record linkage algorithms , 2017, Statistics and Computing.

[52]  Anita Lis-Śledziona Petrophysical rock typing and permeability prediction in tight sandstone reservoir , 2019, Acta Geophysica.

[53]  Fred A. Hamprecht,et al.  ilastik: interactive machine learning for (bio)image analysis , 2019, Nature Methods.

[54]  S. Rahman,et al.  An Analytical Model of Apparent Gas Permeability for Tight Porous Media , 2015, Transport in Porous Media.

[55]  Christoph H. Arns,et al.  Super resolution reconstruction of μ-CT image of rock sample using neighbour embedding algorithm , 2018 .

[56]  Robert Jenssen,et al.  A Scatter-Based Prototype Framework and Multi-Class Extension of Support Vector Machines , 2012, PloS one.

[57]  Shervan Fekri Ershad,et al.  Texture image analysis and texture classification methods - A review , 2019, ArXiv.

[58]  Shuyu Sun,et al.  Multiscale pore structure characterization based on SEM images , 2021 .

[59]  Weisheng Wang,et al.  A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm , 2017, Sensors.

[60]  Yaokun Wu,et al.  Machine learning assisted segmentation of scanning electron microscopy images of organic-rich shales with feature extraction and feature ranking , 2020, Machine Learning for Subsurface Characterization.

[61]  J. R. Fulljames,et al.  Fault seal processes: systematic analysis of fault seals over geological and production time scales , 1997 .

[62]  Laura Diosan,et al.  Improving classification performance of Support Vector Machine by genetically optimising kernel shape and hyper-parameters , 2010, Applied Intelligence.

[63]  A. Sheppard,et al.  Grain Partitioning and its Applications , 2010 .